Antigen Rapid Diagnostic Tests for Community Identification of Severe Acute Respiratory Syndrome Coronavirus 2

Background: Background: Testing with antigen-detecting rapid diagnostic tests (Ag-RDTs), including in asymptomatic individuals, has the potential to promptly identify more Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infections and consequently decrease spread of coronavirus-19 disease at the community level. In addition, rapid test results are important for immediate clinical management and isolation of patients with SARS-CoV-2 infection, and for contact tracing and quarantining of contacts. Data on SARS-CoV-2 infection rates, the acceptability of Ag-RDT, and the cost of conducting widespread testing in these communities are limited in Africa. Study Aim and Objectives: To generate evidence evaluating the use of Ag-RDTs for community identification of SARS-CoV-2 infections within large gathering venues such as work places, schools, places of worship, and markets. The primary objective is to determine the SARS-CoV-2 case detection rate through a mass testing approach in large gatherings. Secondary objectives include determining the proportion of asymptomatic and symptomatic infections detected, acceptance of mass SARS-CoV-2 Ag-RDT testing, the prevalence of circulating variants, and the cost of implementing this community testing strategy. Study Design: The investigators propose a serial cross-sectional study design targeting approximately 15,000 persons, who will be offered testing in up to 50 different high attendance venues of Kiambu County that will be identified as possible points of community-based transmission. The study will follow an opt-in consent approach, with those accepting to participate providing additional information to the trained research assistant and/or health worker. Outcome: Evidence will be generated to provide recommendations to the Kenya Ministry of Health, and more broadly to inform the field on the use of Ag-RDTs for large scale community screening by identifying best practices and stratifying risk areas for community